Age and Gender.
A number of studies have been conducted on English-based age and gender detection, including  [1]}, [2]}, [3]}, [4]}, [5]}. Many of these works use feature engineering such as text n-gram and topic models [6]}, [7]}. In these works, age is either cast as a multi-class classification task with, e.g., labels from the set {10-19, 20-29, 30-39} or as a regression task [8]}. Other works model age with both classification and regression combined [9]}. With rare exceptions [10]}, [11]}, we do not know of work on Arabic targeting age and gender.
